The Innovation Yet To Come

Is #AI just the latest progression of IT value?

Or the next transformational force that will reshape the business landscape?

And if so, will it be the most profound yet?

I think the latter – it’s a story of the multiplier effect of three key factors:

The Basics x The Fuel x The Future.

The Basics

Structured programming has entered a phase of diminishing returns. Humans are algorithmic. We sequence through steps in a probabilistic manner to accomplish things. The advent of computers allowed us to program repeatable steps to become more productive. We then interconnected them, infused interactive experiences, enabled anywhere access, instrumented real-time data, and created new economics with #cloud / #XaaS.? But today's algorithms are largely PRE-programmed unable to iteratively RE-program themselves to continuously improve outcomes. This inherently creates limits that will render structured programming as powerless to solve future problems. ?

AI promises to change this, the promise-of-value is exponential larger. AI algorithms can now take unthinkable amounts of data and learn new sequences of steps and iteratively generate more sophisticated versions of themselves. They'll be able to understand language, reason, navigate the sensory world, and manipulate “objects” to help humans accomplish complex things. With this, AI will deliver more value per dollar invested than any technology we’ve seen so far. The scale of innovation that is yet to come is, perhaps, unprecedented.

The Fuel

The investment indicators are off the scale [1]. Put aside that 9 in 10 businesses are accelerating spend, building off $189B already invested. And that PE has now exceeded $250B. Incredibly, these investments are already 7x the size of the 2024 AI tech market projected to grow at a 35% CAGR.[5].

Focus instead on the AI skill market [2] . AI jobs are already at historic levels relative to the typical technology adoption curve. AI jobs represent the largest job creation category as a fraction of overall employment at 2.3% (up from 0.5% in 2015) and will expand share as the #1 job growth category in the years ahead.

But the real story is in AI research jobs [3].? A whopping 15% of AI jobs are in ML research, as compared to 2% for cloud or 4% for IoT. From here, researchers are projected to grow 22% vs. only 4% for all occupations. ?All said, the fuel is in place to spark unprecedented innovation in the years to come.

“ML is the only technology at the top in both number and percentage of research job postings” - NBER/GPT

The Future? ?

We’re still in the infancy phase of AI’s impact. Today’s AI is largely anchored in narrow use cases, NLP and correlative inferencing, the lowest forms of potential impact. While #GenAI is now emerging on the scene, it’s the future waves of innovation that will likely deliver the truly profound impact. They include:

• Causal Inferencing – Future AI systems will explore “cause and effect” - the dynamics of “why” things happen, what can be done to change outcomes, and the consequences of possible interventions. Humans are causal by nature, so AI needs to also become causal by nature. Read the book on Causal AI by Judith Hurwitz and John Thompson to learn more.
• ?Conversational Explainability – The inability of AI to explain what they are saying, doing, recommending, or predicting as a core inhibitor. Future AI systems will be able to engage with humans to collaboratively reason, evaluate alternate scenarios and to ultimately produce optimal outcomes.
• ?Autonomous RegTech – AI regulations have expanded 5x yearly since 2020 with no end in sight. Future AI systems will learn the regulatory landscape, create self-regulating knowledge, anticipate consequences and inhibit improper behavior. Just like the human Prefrontal Cortex.
• Regenerative Diagnostics?– “Garbage in, garbage out” is a big problem with today’s AI. The incredible volume, velocity, variety, and veracity of their data sets are impossible to pre-program, nor even to comprehend. Future AI will score, repair, cleanse and regenerate their data sets to continuously improve their health, mimicking the human immune system.

?The Most Profound Transformation Yet? ?

For the reasons outlined above and what I have learned from decades of engaging a vast network of businesses, technology innovators and business strategists, I think we in for the most profound transformation yet.

With the new waves of AI innovation that are sure to come, we’ll see a technological capability on a scale we have not seen before. And it’s my bet that a new generation of tech-savvy, risk-tolerant business leaders will leverage these advancements to totally reinvent how their businesses operate, create value, and engage the world.

And, in turn, reshaping the business landscape (and society) on a scale that is hard to conceptualize today. We are in for one hell of a ride! Stay tuned ...?

Scott Hebner

Sources:

[1] The AI Index Report - The Economy, Stanford University

[2] World Economic Forum Future of Jobs Report

[3] National Bureau of Economic Research (GPT)

[4] Wharton AI for Business Course Materials